Transcription factors are generally the termini of signaling cascades. As such, they are the ultimate mediators of change in cell function resulting from changes in the cellular environment. Inappropriate or unregulated expression of transcription factors has been implicated in many diseases, including cancer, AIDS, and Type II diabetes. As such, a complete understanding of the transcription factor profile of a cell at any time would provide an exquisitely detailed depiction of the current function of that cell as well as strong indications of functional changes that may occur in the future. Despite the importance of this information and its predictive value, few tools exist that provide sensitive, reproducible, and parallel transcription factor expression analysis. It is proposed to address this significant need, leveraging validated tools from genomics. Our proposed method will combine solution-phase detection of transcription factors with a PCR-based readout to achieve detection limits of hundreds of transcription factor molecules per sample. As we have begun to characterize the signaling events that occur upon administration of cytokines and fatty acids to hepatic cells, a model of Type II diabetes, we will use this system as a model system for development and refinement of the analytical technique. The specific aims of the proposed work are to i) quantify in vitro association of TFs to their recognition sequences in MB-cassettes;ii) determine the lower detection limits for measurements of individual and multiple TFs;iii) measure TF level changes following stimulation of HepG2 cells in culture. Transcription factors are cellular proteins that cells call upon to respond to changes in their environment. Altered transcription factor expression is often a hallmark of a disease condition. Our proposed work will provide a better means of measuring global changes in transcription factor expression and, in turn, allow for greater understanding of and better treatment of disease.